Package: diffudist
Title: Diffusion Distance for Complex Networks
Version: 1.0.0
Authors@R: c(
    person(given = "Giulia",
           family = "Bertagnolli",
           role = c("aut", "cre"),
           email = "giulia.bertagnolli@gmail.com",
           comment = c(ORCID = "0000-0001-8637-0632")),
    person(given = "Manlio", 
           family = "De Domenico", 
           role = "aut", 
           email = "manlio.dedomenico@gmail.com", 
           comment = c(ORCID = "0000-0001-5158-8594"))
           )
URL: https://gbertagnolli.github.io/diffudist/
BugReports: https://github.com/gbertagnolli/diffudist/issues/
Description: Enables the evaluation of diffusion distances for complex single-layer networks.
    Given a network one can define different types of Laplacian (or transition)
    matrices corresponding to different continuous-time random walks dynamics on the network. 
    This package enables the evaluation of Laplacians, stochastic matrices, and the 
    corresponding diffusion distance matrices. The metric structure induced by the network-driven
    process is richer and more robust than the one given by shortest-paths and allows to study 
    the geometry induced by different types of diffusion-like communication mechanisms taking 
    place on complex networks. 
    For more details see: De Domenico, M. (2017) <doi:10.1103/physrevlett.118.168301> and 
    Bertagnolli, G. and De Domenico, M. (2021) <doi:10.1103/PhysRevE.103.042301>.
Depends: R (>= 3.5.0)
Imports: expm, ggdendro, ggplot2, grid, igraph, Matrix, stats, Rcpp (>=
        1.0.7), reshape2, rlang, viridis
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, cowplot, parallelDist, strex, tidyr, rmarkdown
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.1.2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-11-29 09:47:25 UTC; giulia
Author: Giulia Bertagnolli [aut, cre] (<https://orcid.org/0000-0001-8637-0632>),
  Manlio De Domenico [aut] (<https://orcid.org/0000-0001-5158-8594>)
Maintainer: Giulia Bertagnolli <giulia.bertagnolli@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-30 08:20:06 UTC
Built: R 4.0.5; x86_64-w64-mingw32; 2022-04-21 12:29:24 UTC; windows
Archs: i386, x64
